Spatially Addressable Multiplex Biodetection by Calibrated Micro/Nanostructured Surfaces.

A challenge of any biosensing technology is the detection of very low concentrations of analytes. The fluorescence interference contrast (FLIC) technique improves the fluorescence-based sensitivity by selectively amplifying, or suppressing, the emission of a fluorophore-labeled biomolecule immobilized on a transparent layer placed on top of a mirror basal surface. The standing wave of the reflected emission light means that the height of the transparent layer operates as a surface-embedded optical filter for the fluorescence signal. FLIC extreme sensitivity to wavelength is also its main problem: small, e.g., 10 nm range, variations of the vertical position of the fluorophore can translate in unwanted suppression of the detection signal. Herein, we introduce the concept of quasi-circular lenticular microstructured domes operating as continuous-mode optical filters, generating fluorescent concentric rings, with diameters determined by the wavelengths of the fluorescence light, in turn modulated by FLIC. The critical component of the lenticular structures was the shallow sloping side wall, which allowed the simultaneous separation of fluorescent patterns for virtually any fluorophore wavelength. Purposefully designed microstructures with either stepwise or continuous-slope dome geometries were fabricated to modulate the intensity and the lateral position of a fluorescence signal. The simulation of FLIC effects induced by the lenticular microstructures was confirmed by the measurement of the fluorescence profile for three fluorescent dyes, as well as high-resolution fluorescence scanning using stimulated emission depletion (STED) microscopy. The high sensitivity of the spatially addressable FLIC technology was further validated on a diagnostically important target, i.e., the receptor-binding domain (RBD) of the SARS-Cov2 via the detection of RBD:anti-S1-antibody.

Nanolithographic Fabrication Technologies for Network-Based Biocomputation Devices.

Network-based biocomputation (NBC) relies on accurate guiding of biological agents through nanofabricated channels produced by lithographic patterning techniques. Here, we report on the large-scale, wafer-level fabrication of optimized microfluidic channel networks (NBC networks) using electron-beam lithography as the central method. To confirm the functionality of these NBC networks, we solve an instance of a classical non-deterministic-polynomial-time complete ("NP-complete") problem, the subset-sum problem. The propagation of cytoskeletal filaments, e.g., molecular motor-propelled microtubules or actin filaments, relies on a combination of physical and chemical guiding along the channels of an NBC network. Therefore, the nanofabricated channels have to fulfill specific requirements with respect to the biochemical treatment as well as the geometrical confienement, with walls surrounding the floors where functional molecular motors attach. We show how the material stack used for the NBC network can be optimized so that the motor-proteins attach themselves in functional form only to the floor of the channels. Further optimizations in the nanolithographic fabrication processes greatly improve the smoothness of the channel walls and floors, while optimizations in motor-protein expression and purification improve the activity of the motor proteins, and therefore, the motility of the filaments. Together, these optimizations provide us with the opportunity to increase the reliability of our NBC devices. In the future, we expect that these nanolithographic fabrication technologies will enable production of large-scale NBC networks intended to solve substantially larger combinatorial problems that are currently outside the capabilities of conventional software-based solvers.

Correction to 'Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problems'.

[This corrects the article DOI: 10.1098/rsfs.2018.0034.].

Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problems.

On-chip network-based computation, using biological agents, is a new hardware-embedded approach which attempts to find solutions to combinatorial problems, in principle, in a shorter time than the fast, but sequential electronic computers. This analytical review starts by describing the underlying mathematical principles, presents several types of combinatorial (including NP-complete) problems and shows current implementations of proof of principle developments. Taking the subset sum problem as example for in-depth analysis, the review presents various options of computing agents, and compares several possible operation 'run modes' of network-based computer systems. Given the brute force approach of network-based systems for solving a problem of input size C, 2C solutions must be visited. As this exponentially increasing workload needs to be distributed in space, time, and per computing agent, this review identifies the scaling-related key technological challenges in terms of chip fabrication, readout reliability and energy efficiency. The estimated computing time of massively parallel or combinatorially operating biological agents is then compared to that of electronic computers. Among future developments which could considerably improve network-based computing, labelling agents 'on the fly' and the readout of their travel history at network exits could offer promising avenues for finding hardware-embedded solutions to combinatorial problems.

Parallel computation with molecular-motor-propelled agents in nanofabricated networks.

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.

Fluorescence biosensing micropatterned surfaces based on immobilized human acetylcholinesterase.

Human acetylcholinesterase (AChE) is a widely studied target enzyme in drug discovery for Alzheimer's disease (AD). In this paper we report evaluation of the optimum structure and chemistry of the supporting material for a new AChE-based fluorescence sensing surface. To achieve this objective, multilayered silicon wafers with spatially controlled geometry and chemical diversity were fabricated. Specifically, silicon wafers with silicon oxide patterns (SiO(2)/Si wafers), platinum-coated silicon wafers with SiO(2) patterns (SiO(2)/Pt/Ti/Si wafers), and Pt-coated wafers coated with different thicknesses of TiO(2) and SiO(2) (SiO(2)/TiO(2)/Pt/Ti/Si wafers) were labelled with the fluorescent conjugation agent HiLyte Fluor 555. Selection of a suitable material and the optimum pattern thickness required to maximize the fluorescence signal and maintain chemical stability was performed by confocal laser-scanning microscopy (CLSM). Results showed that the highest signal-to-background ratio was always obtained on wafers with 100 nm thick SiO(2) features. Hence, these wafers were selected for covalent binding of human AChE. Batch-wise kinetic studies revealed that enzyme activity was retained after immobilization. Combined use of atomic-force microscopy and CLSM revealed that AChE was homogeneously and selectively distributed on the SiO(2) microstructures at a suitable distance from the reflective surface. In the optimum design, efficient fluorescence emission was obtained from the AChE-based biosensing surface after labelling with propidium, a selective fluorescent probe of the peripheral binding site of AChE.

The influence of nanoscale grooved substrates on osteoblast behavior and extracellular matrix deposition.

To fight bone diseases characterized by poor bone quality like osteoporosis and osteoarthritis, as well as in reconstructive surgery, there is a need for a new generation of implantable biomaterials. It is envisioned that implant surfaces can be improved by mimicking the natural extracellular matrix of bone tissue, which is highly a organized nano-composite. In this study we aimed to get a better understanding of osteoblast response to nanometric grooved substrates varying in height, width and spacing. A throughput screening biochip was created using electron beam lithography. Subsequently, uniform large-scale nanogrooved substrates were created using laser interference lithography and reactive ion etching. Results showed that osteoblasts were responsive to nanopatterns down to 75 nm in width and 33nm in depth. SEM and TEM studies showed that an osteoblast-driven calcium phosphate (CaP) mineralization was observed to follow the surface pattern dimensions. Strikingly, aligned mineralization was found on even smaller nanopatterns of 50 nm in width and 17 nm in depth. A single cell based approach for real time PCR demonstrated that osteoblast-specific gene expression was increased on nanopatterns relative to a smooth control. The results indicate that nanogrooves can be a very promising tool to direct the bone response at the interface between an implant and the bone tissue.